diff --git a/components/kubeflow/kfserving/Dockerfile b/components/kubeflow/kfserving/Dockerfile
index 8021a63e12b..59553754aa6 100644
--- a/components/kubeflow/kfserving/Dockerfile
+++ b/components/kubeflow/kfserving/Dockerfile
@@ -1,6 +1,6 @@
 FROM python:3.6-slim
 
-RUN pip3 install kubernetes==10.0.1 kfserving==0.3.0 requests==2.22.0 Flask==1.1.1 flask-cors==3.0.8
+RUN pip3 install kubernetes==10.0.1 kfserving==0.4.1 requests==2.22.0 Flask==1.1.1 flask-cors==3.0.8
 
 ENV APP_HOME /app
 COPY src $APP_HOME
diff --git a/components/kubeflow/kfserving/component.yaml b/components/kubeflow/kfserving/component.yaml
index ec6da8ff006..fff3764413c 100644
--- a/components/kubeflow/kfserving/component.yaml
+++ b/components/kubeflow/kfserving/component.yaml
@@ -22,7 +22,7 @@ outputs:
   - {name: Service Endpoint URI, type: String,                      description: 'URI of the deployed prediction service..'}
 implementation:
   container:
-    image: aipipeline/kfserving-component:v0.3.0
+    image: aipipeline/kfserving-component:v0.4.1
     command: ['python']
     args: [
       -u, kfservingdeployer.py,
diff --git a/components/kubeflow/kfserving/src/kfservingdeployer.py b/components/kubeflow/kfserving/src/kfservingdeployer.py
index c1f64dd22ee..a64db854814 100644
--- a/components/kubeflow/kfserving/src/kfservingdeployer.py
+++ b/components/kubeflow/kfserving/src/kfservingdeployer.py
@@ -32,7 +32,7 @@
 from kfserving import V1alpha2SKLearnSpec
 from kfserving import V1alpha2XGBoostSpec
 from kfserving.models.v1alpha2_onnx_spec import V1alpha2ONNXSpec
-from kfserving import V1alpha2TensorRTSpec
+from kfserving import V1alpha2TritonSpec
 from kfserving import V1alpha2CustomSpec
 from kfserving import V1alpha2InferenceServiceSpec
 from kfserving import V1alpha2InferenceService
@@ -79,11 +79,11 @@ def EndpointSpec(framework, storage_uri, service_account, min_replicas, max_repl
     elif framework == "onnx":
         endpointSpec.predictor.onnx = V1alpha2ONNXSpec(storage_uri=storage_uri)
         return endpointSpec
-        
-    elif framework == "tensorrt":
-        endpointSpec.predictor.tensorrt = V1alpha2TensorRTSpec(storage_uri=storage_uri)
+
+    elif framework == "triton":
+        endpointSpec.predictor.triton = V1alpha2TritonSpec(storage_uri=storage_uri)
         return endpointSpec
-        
+      
     else:
         raise ("Error: No matching framework: " + framework)
 
@@ -429,12 +429,14 @@ def update(kfsvc, model_name, namespace):
                 exit(1)
     try:
         print(
-            model_status["status"]["url"] + " is the knative domain."
+            model_status["status"]["address"]["url"] + " is the knative domain."
         )
+       
         print("Sample test commands: \n")
         # model_status['status']['url'] is like http://flowers-sample.kubeflow.example.com/v1/models/flowers-sample
+
         print(
-            "curl -v -X GET %s" % model_status["status"]["url"]
+            "curl -v -X GET %s" % model_status["status"]["address"]["url"]
         )
 
         print("\nIf the above URL is not accessible, it's recommended to setup Knative with a configured DNS.\n"\